Record information data is increasingly important in the modern world. With the advent of computer technology the ability for individuals and entities to store and retrieve data has become increasingly more commonplace. Often this storage involves the use of databases which may be quite large.
Especially in the area of commerce, record data such as customer information is often highly guarded. Indeed companies exist for the sole propose of mining customer data and developing lists of individuals that are tailored for specific product or service offerings. This data and its organization may actually be a trade secret that, if revealed, would weaken a company's competitive edge.
For example, in a Universe of people defined as the United States, a company may have compiled detailed information records regarding past products purchased. Likewise another company may have compiled detailed information records regarding past travel patterns.
As important to each company's business as it is to keep these records secret, there may well be marketing opportunities that would benefit both companies if overlaps in the record sets were known.
As different companies may well use different databases, a direct comparison of the data may not be an easy task, requiring data reformat and possible migration from one platform to another. In addition, in some comparison scenarios it may be possible to determine the other party's data by systematic testing. The value of the data and the risk of exposure or exploitation may be viewed as so great and potentially so damaging that attempting a comparison is not viewed as viable.
In another setting there may be issues regarding personal privacy, yet a very real need to compare and identify individuals and/or information. Likewise, there are often needs to compare private documents, but not inadvertently reveal the contents of the documents.
To some extent, neutral third parties may be engaged to perform the comparison such that neither of the data-holding parties has an opportunity for first-hand review. As effective as such an exercise may be, the neutral third party does, of course, have access to both sets of data and must be well trusted. In some instances it may be effective to use unique values, such as hash values, to confirm perfect matches between data; however; as the change of one element will result in an entirely different hash, such a comparison is truly only practical for perfect match situations.
In certain instances, hash values may also be used to confirm the presence of one or more members within a set. However, in such an instance, if the members of the universe are known, it is possible to systematically test to see if each of these members is in the target set. In so doing the anonymity of the set members is lost.
Hence, there is a need for a method to permit the comparison of set members where the sets are not necessarily identical and where the members of the sets are not openly compared so as to overcome one or more of the drawbacks identified above.